This function provides a number of descriptives about your data, similar to what SPSS's DESCRIPTIVES (often called with DESCR) does.

```
descr(x, digits = 4, errorOnFactor = FALSE,
include = c("central tendency", "spread", "range",
"distribution shape", "sample size"),
maxModes = 1,
t = FALSE, conf.level=.95,
quantileType = 2);
```

x

The vector for which to return descriptives.

digits

The number of digits to round the results to when showing them.

errorOnFactor

Whether to show an error when the vector is a factor, or just show the frequencies instead.

include

Which elements to include when showing the results.

maxModes

Maximum number of modes to display: displays "multi" if more than this number of modes if found.

t

Whether to transpose the dataframes when printing them to the screen (this is easier for users relying on screen readers).

conf.level

Confidence of confidence interval around the mean in the central tendency measures.

quantileType

The type of quantiles to be used to compute the interquartile range (IQR). See `quantile`

for more information.

A list of dataframes with the requested values.

Note that R (of course) has many similar functions, such as `summary`

,
`describe`

in the excellent `psych`

package.

The Hartigans' Dip Test may be unfamiliar to users; it is a measure of uni- vs. multidimensionality, computed by `dip.test`

from the `dip.test`

package. Depending on the sample size, values over .025 can be seen as mildly indicative of multimodality, while values over .05 probably warrant closer inspection (the p-value can be obtained using `dip.test`

; also see Table 1 of Hartigan & Hartigan (1985) for an indication as to critical values).

Hartigan, J. A.; Hartigan, P. M. The Dip Test of Unimodality. Ann. Statist. 13 (1985), no. 1, 70--84. doi:10.1214/aos/1176346577. http://projecteuclid.org/euclid.aos/1176346577.

```
# NOT RUN {
descr(mtcars$mpg);
# }
```

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